What is Value Chain Simulation Modelling?

VCSM is a simulation-based method that helps policymakers understand how new technologies might affect different actors across a sector — economically, socially and environmentally. It’s built on the foundations of the HM Treasury Green Book and shares many of the same principles: estimating both Net Present Value (NPV), applying discount rates, and using monetised and non-monetised impacts where appropriate, and Gross Domestic Product (GDP), considering both demand and supply-side impacts.

What sets VCSM apart is how it generates those estimates — particularly when hard data is limited or future behaviours are unknown.

Here’s how it works:

• Actor-Based Value Chains: VCSM starts by mapping the value flows between different actors (e.g. consumers, sectors, regulators), that are involved in delivering the technology.
• Cost and Benefit Mapping: Through stakeholder interviews, surveys and market research, we identify and validate the potential impacts arising from these interactions — ranging from transaction cost savings and time efficiencies to behavioural changes and wider social benefits.
• Apply Confidence Grades: We agree the assumptions for the model and adjust them for optimism bias, based on “Confidence Grades” assigned to assumption sources.
• Scenario-Based Simulation: Rather than producing a single estimate, VCSM uses Monte Carlo simulation to test thousands of possible futures. This helps us explore the full range of outcomes, identify key assumptions, and quantify uncertainty around each forecast.

This results in a flexible but rigorous approach that works with the realities of emerging tech: partial data, behavioural dependencies, and systems still in development.

Why Should Policy Makers Use Value Chain Simulation Modelling?

We see five main benefits of the VCSM approach.

1. Aligned with Green Book Standards

While VCSM is more dynamic than standard CBA, it is firmly grounded in Green Book guidance. We apply the same principles of public value, use the Social Time Preference Rate to discount future values, and include both market and non-market effects where justified.

2. Built for Uncertainty

Rather than relying on point estimates, VCSM simulates a distribution of outcomes based on defined confidence levels. This gives policymakers a clear view of what’s likely, what’s possible, and where risks or opportunities lie. It also allows comparison of different policy options on the basis of both expected value and volatility.

3. System-Wide Perspective

Instead of modelling just one organisation or sector, VCSM maps the whole system: data flows, incentive structures, and interactions between actors. This reveals second-order impacts that might otherwise be missed — such as spill-overs to consumers, supply chain effects, or disincentives for participation.

4. Inclusive of Intangible and Indirect Value

Because VCSM models more uncertain impacts, such as willingness to pay, time saved, or health improvements, it can account for a richer set of outcomes than many conventional tools. Our Confidence Grades system ensures we handle these more uncertain areas appropriately. This is especially useful in areas like digital policy, consumer tech, or environmental regulation, where benefits are real but either not always monetised in market prices or dependent on things like user adoption.

5. Supports Better Policy Design

By showing not just what the average outcome is, but the range of possible outcomes and why they arise, VCSM can help policymakers fine-tune scheme design. For example, it can clarify which actors bear the most cost, barriers to adoption, and where legislation or incentives could unlock greater benefits.

A Forward-Looking Tool for Emerging Technologies and Innovation

The public sector is increasingly being asked to anticipate the impacts of technologies that haven’t yet reached mass adoption. Whether in smart data, artificial intelligence (AI) governance, green finance or digital infrastructure, appraisal teams need tools that reflect how innovation really unfolds — messily, unevenly, and with a mix of winners and losers.

VCSM doesn’t claim to eliminate uncertainty. But by acknowledging it, simulating it, and analysing it transparently, it provides a better foundation for action. It helps decision-makers answer not just “What’s the expected value?” but “What are the interfaces, risks and dependencies?”, “Who benefits and who loses?” and “How can we design this better?”

Want to Learn More?

If you’re working on an emerging tech policy and need support to assess its value — or want to hear how others are doing it — get in touch with David Chappell and the team at The PSC. We’d be happy to share insights from our modelling work and explore how VCSM could support your objectives.